Purpose & Assumptions The purpose of this guide is to describe the primary differences in analyzing sequences generated using the Earth Microbiome Project (EMP) or standard Illumina protocols. In other words, this post will describe the practical aspects and applications with respect to analyzing the data, rather than the theory behind the process, study design, etc. At the Center for Quantitative Life Sciences (CQLS) at OSU, we explicitly support two 16S sequencing protocols.
In my previous posts here and here, I showed you how to maintain your own R install, and update the libraries after you update your own R version. Today, I’m going to cover an easier topic, how to use the system R installs. We have a variety of versions of R on the infrastructure. By default, you are most likely to use the system version of R that comes with CentOS 7, which is found in /usr/bin/R and /bin/R, which happens to be 3.
Preface So you’ve requested an account on the CQLS infrastructure and have the account information email in your inbox and you don’t know where to start. Well, you’re in the right place! Get familiar with the CQLS infrastructure policies before you begin your journey. Ideally, you would have a more senior member of your lab or maybe another grad student in your department to go to for the ins-and-outs of the infrastructure.
In my previous post about R I showed you how to install a local R version and set up your R_LIBS environment variable so that it points to the new R version. If you already had a working R install, you may be wondering how you can get access to all of the R libraries that you previously installed. You have several options. You have to decide if you ever want to fall back on the previous R version if something breaks in the current R version.
Summary You want to maintain your own R packages on the infrastructure? Great! Let’s get you set up with your own R install so that you can update even the core packages whenever you need an update. Downloading R Visit https://ftp.osuosl.org/pub/cran/ and download the latest release (as of writing, v 3.6.1). Generally I maintain a path similar to this: /nfs3/CGRB/home/davised/opt/downloads for downloading my source code. Your path would likely include your lab name and your own user name.
Download the Rmd file Introduction Dataset examined is from this file https://www.mothur.org/MiSeqDevelopmentData/StabilityNoMetaG.tar The full MiSeqSOP, a partial dataset is discussed here on the mothur website: https://www.mothur.org/wiki/MiSeq_SOP Here is a small excerpt from the site that describes the study design: Starting out we need to first determine, what is our question? The Schloss lab is interested in understanding the effect of normal variation in the gut microbiome on host health. To that end we collected fresh feces from mice on a daily basis for 365 days post weaning (we're accepting applications).